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Data Transmission Scheme Using Mobile Sink in Static Wireless Sensor Network
Ahmad, Awais,Rathore, M. Mazhar,Paul, Anand,Chen, Bo-Wei Hindawi Limited 2015 Journal of sensors Vol.2015 No.-
<P>Multihop communication in wireless sensor network (WSN) brings new challenges in reliable data transmission. Recent work shows that data collection from sensor nodes using mobile sink minimizes multihop data transmission and improves energy efficiency. However, due to continuous movements, mobile sink has limited communication time to collect data from sensor nodes, which results in rapid depletion of node’s energy. Therefore, we propose a data transmission scheme that addresses the aforementioned constraints. The proposed scheme first finds out the group based region on the basis of localization information of the sensor nodes and predefined trajectory information of a mobile sink. After determining the group region in the network, selection of master nodes is made. The master nodes directly transmit their data to the mobile sink upon its arrival at their group region through restricted flooding scheme. In addition, the agent node concept is introduced for swapping of the role of the master nodes in each group region. The master node when consuming energy up to a certain threshold, neighboring node with second highest residual energy is selected as an agent node. The mathematical analysis shows that the selection of agent node maximizes the throughput while minimizing transmission delay in the network.</P>
Ahmad, Rizwan,Anwar, Muhammad Shoaib,Kim, Jae,Song, In-Hyuck,Abbas, Syed Zaighum,Ali, Syed Ahmad,Ali, Fahad,Ahmad, Jamil,Bin Awais, Hasan,Mehmood, Mazhar Elsevier 2016 CERAMICS INTERNATIONAL Vol.42 No.16
<P><B>Abstract</B></P> <P>Bimodal porous structures were prepared by combining conventional sacrificial template and partial sintering methods. These porous structures were analysed by comparing pore characteristics and gas permeation properties of alumina/mullite specimens sintered at different temperatures. The pore characteristics were investigated by SEM, mercury porosimetry, and capillary flow porosimetry. A bimodal pore structure was observed. One type of pore was induced by starch, which acted as a sacrificial template. The other pore type was due to partial sintering. The pores produced by starch were between 2 and 10µm whereas those produced by partial sintering exhibited pore size of 0.1–0.5µm. The effects of sintering temperature on porosity, gas permeability, and mullite phase formation were studied. The formation of the mullite phase was confirmed by XRD. Compressive strengths of 37.9MPa and 12.4MPa with porosities of 65.3% and 70% were achieved in alumina and mullite specimens sintered at 1600°C.</P>
Toward modeling and optimization of features selection in Big Data based social Internet of Things
Ahmad, Awais,Khan, Murad,Paul, Anand,Din, Sadia,Rathore, M. Mazhar,Jeon, Gwanggil,Choi, Gyu Sang North-Holland 2018 Future generations computer systems Vol.82 No.-
<P><B>Abstract</B></P> <P>The growing gap between users and the Big Data analytics requires innovative tools that address the challenges faced by big data volume, variety, and velocity. Therefore, it becomes computationally inefficient to analyze and select features from such massive volume of data. Moreover, advancements in the field of Big Data application and data science poses additional challenges, where a selection of appropriate features and High-Performance Computing (HPC) solution has become a key issue and has attracted attention in recent years. Therefore, keeping in view the needs above, there is a requirement for a system that can efficiently select features and analyze a stream of Big Data within their requirements. Hence, this paper presents a system architecture that selects features by using Artificial Bee Colony (ABC). Moreover, a Kalman filter is used in Hadoop ecosystem that is used for removal of noise. Furthermore, traditional MapReduce with ABC is used that enhance the processing efficiency. Moreover, a complete four-tier architecture is also proposed that efficiently aggregate the data, eliminate unnecessary data, and analyze the data by the proposed Hadoop-based ABC algorithm. To check the efficiency of the proposed algorithms exploited in the proposed system architecture, we have implemented our proposed system using Hadoop and MapReduce with the ABC algorithm. ABC algorithm is used to select features, whereas, MapReduce is supported by a parallel algorithm that efficiently processes a huge volume of data sets. The system is implemented using MapReduce tool at the top of the Hadoop parallel nodes with near real-time. Moreover, the proposed system is compared with Swarm approaches and is evaluated regarding efficiency, accuracy and throughput by using ten different data sets. The results show that the proposed system is more scalable and efficient in selecting features.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Presents an architecture for Social Internet of Things. </LI> <LI> Modeling and optimization of Big Data. </LI> <LI> System architecture based on ABC. </LI> <LI> MapReduce with ABC to enhance system efficiency. </LI> </UL> </P>
Context-Aware Mobile Sensors for Sensing Discrete Events in Smart Environment
Ahmad, Awais,Rathore, M. Mazhar,Paul, Anand,Hong, Won-Hwa,Seo, HyunCheol Hindawi Limited 2016 Journal of sensors Vol.2016 No.-
<P>Over the last few decades, several advancements in the field of smart environment gained importance, so the experts can analyze ideas for smart building based on embedded systems to minimize the expense and energy conservation. Therefore, propelling the concept of smart home toward smart building, several challenges of power, communication, and sensors’ connectivity can be seen. Such challenges distort the interconnectivity between different technologies, such as Bluetooth and ZigBee, making it possible to provide the continuous connectivity among different objects such as sensors, actuators, home appliances, and cell phones. Therefore, this paper presents the concept of smart building based on embedded systems that enhance low power mobile sensors for sensing discrete events in embedded systems. The proposed scheme comprises system architecture that welcomes all the mobile sensors to communicate with each other using a single platform service. The proposed system enhances the concept of smart building in three stages (i.e., visualization, data analysis, and application). For low power mobile sensors, we propose a communication model, which provides a common medium for communication. Finally, the results show that the proposed system architecture efficiently processes, analyzes, and integrates different datasets efficiently and triggers actions to provide safety measurements for the elderly, patients, and others.</P>